Research on Multi-Objective reactive power optimization based on modified Particle Swarm Optimization algorithm

Author

Wu, Jianhua ; Li, Nan ; He, Lihong ; Yin, Bin ; Guo, Jianhua ; Liu, Yaqiong

Author_Institution

Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2010

fDate

26-28 May 2010

Firstpage

477

Lastpage

480

Abstract

This paper proposes modified Multi-Objective Particle Swarm Optimization (MPSO) algorithm based on Pareto solution to overcome the conventional MPSO algorithm can easily fall into its local maximum value and improve the diversity of solution set. This algorithm is composition of a modified Tabu Search with Multi-Objective Particle Swarm Optimization (TSMPSO). With this algorithm Establishing the memory devices- taboo list of global optimal solution, Store the history of the particle that is selected to be the optimal global. And through this approach to strengthen performance of particle swarm optimization in global and local searching. TSMPSO is simple and easy to implement. Simulation results of IEEE 30-bus system show that this algorithm can enhance power system voltage stability, meanwhile economic operation of power system is also implemented, thus the effectiveness and superiority of TSMPSO algorithm are verified.

Keywords

Pareto optimisation; particle swarm optimisation; power system stability; reactive power; search problems; IEEE 30-bus system; Pareto solution; memory devices taboo list; multiobjective particle swarm optimization; multiobjective reactive power optimization; power system voltage stability; tabu search; Mathematical model; Pareto optimization; Particle swarm optimization; Power generation economics; Power system economics; Power system security; Power system simulation; Power system stability; Reactive power; Voltage; MPSO; Multi-Objective Reactive Power Optimization; PSO; TABU; active network loss; voltage stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5499012

Filename

5499012